Statistical Models and Methods for Biomedical and Technical Systems

Descripción:

Deals with the mathematical aspects of survival analysis and reliability as well as other topics, reflecting developments in the following areas: applications in epidemiology; probabilistic and statistical models and methods in reliability; models and methods in survival analysis, longevity, aging, and degradation; and, more. Editor(s): Vonta, Filia; Nikulin, Mikhail; Limnios, Nikolaos; Huber-Carol, Catharine (Universite de Paris). Series: Statistics for Industry and Technology. Num Pages: 592 pages, 55 black & white illustrations, 32 black & white tables, biography. BIC Classification: MBNS; MQW; PBT; PBW. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 261 x 187 x 32. Weight in Grams: 1194. . 2008. 2008th Edition. hardcover. . . . . Books ship from the US and Ireland. N° de ref. del artículo V9780817644642

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Sinopsis:

De la contraportada:

An outgrowth of the "International Conference on Statistical Models for Biomedical and Technical Systems," this book is comprised of contributions from renowned experts, demonstrating the significance of current research on theory, methods, and applications of the field. The contributions, which deal with the mathematical aspects of survival analysis and reliability as well as other topics, are a careful selection of invited and contributed chapters, reflecting recent developments in the following areas:

* Applications in epidemiology

* Estimation and testing for stochastic processes

* Generalizations of the Cox regression model

* Probabilistic and statistical models and methods in reliability

* Semi-parametric inference in survival analysis

* Models and methods in survival analysis, longevity, aging, and degradation

* Nonparametric estimation Goodness-of-fit tests

* Accelerated life models

* Quality of life

* Analysis of censored data

* Adaptive and repeated measurements designs

* Measures of divergence, model selection, and survival models

* New statistical challenges in genomics

The book will be useful to a broad interdisciplinary readership of researchers and practitioners in applied probability and statistics, industrial statistics, biomedicine, biostatistics, and engineering. Practitioners and researchers in academia will gain insight and new ideas for exploring this fertile area of research.